Report on INEX 2008

INEX investigates focused retrieval from structured documents by providing large test collections of structured documents, uniform evaluation measures, and a forum for organizations to compare their results. This paper reports on the INEX 2008 evaluation campaign, which consisted of a wide range of tracks: Ad hoc, Book, Efficiency, Entity Ranking, Interactive, QA, Link the Wiki, and XML Mining.

Automated diagnosis of Age-related Macular Degeneration using greyscale features from digital fundus images

Age-related Macular Degeneration (AMD) is one of the major causes of vision loss and blindness in ageing population. Currently, there is no cure for AMD, however early detection and subsequent treatment may prevent the severe vision loss or slow the progression of the disease. AMD can be classified into two types: dry and wet AMDs. The people with macular degeneration are mostly affected by dry AMD. Early symptoms of AMD are formation of drusen and yellow pigmentation. These lesions are identified by manual inspection of fundus images by the ophthalmologists. It is a time consuming, tiresome process, and hence an automated diagnosis of AMD screening tool can aid clinicians in their diagnosis significantly. This study proposes an automated dry AMD detection system using various entropies (Shannon, Kapur, Renyi and Yager), Higher Order Spectra (HOS) bispectra features, Fractional Dimension (FD), and Gabor wavelet features extracted from greyscale fundus images. The features are ranked using t-test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance (CBBD), Receiver Operating Characteristics (ROC) curve-based and Wilcoxon ranking methods in order to select optimum features and classified into normal and AMD classes using Naive Bayes (NB), k-Nearest Neighbour (k-NN), Probabilistic Neural Network (PNN), Decision Tree (DT) and Support Vector Machine (SVM) classifiers. The performance of the proposed system is evaluated using private (Kasturba Medical Hospital, Manipal, India), Automated Retinal Image Analysis (ARIA) and STructured Analysis of the Retina (STARE) datasets. The proposed system yielded the highest average classification accuracies of 90.19%, 95.07% and 95% with 42, 54 and 38 optimal ranked features using SVM classifier for private, ARIA and STARE datasets respectively. This automated AMD detection system can be used for mass fundus image screening and aid clinicians by making better use of their expertise on selected images that require further examination.

Decision support system for age-related macular degeneration using discrete wavelet transform

Age-related macular degeneration (AMD) affects the central vision and subsequently may lead to visual loss in people over 60 years of age. There is no permanent cure for AMD, but early detection and successive treatment may improve the visual acuity. AMD is mainly classified into dry and wet type; however, dry AMD is more common in aging population. AMD is characterized by drusen, yellow pigmentation, and neovascularization. These lesions are examined through visual inspection of retinal fundus images by ophthalmologists. It is laborious, time-consuming, and resource-intensive. Hence, in this study, we have proposed an automated AMD detection system using discrete wavelet transform (DWT) and feature ranking strategies. The first four-order statistical moments (mean, variance, skewness, and kurtosis), energy, entropy, and Gini index-based features are extracted from DWT coefficients. We have used five (t test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance, receiver operating characteristics curve-based, and Wilcoxon) feature ranking strategies to identify optimal feature set. A set of supervised classifiers namely support vector machine (SVM), decision tree, k -nearest neighbor ( k -NN), Naive Bayes, and probabilistic neural network were used to evaluate the highest performance measure using minimum number of features in classifying normal and dry AMD classes. The proposed framework obtained an average accuracy of 93.70 %, sensitivity of 91.11 %, and specificity of 96.30 % using KLD ranking and SVM classifier. We have also formulated an AMD Risk Index using selected features to classify the normal and dry AMD classes using one number. The proposed system can be used to assist the clinicians and also for mass AMD screening programs.

Utilizing voting systems for ranking user tweets

Twitter is a very popular social network website that allows users to publish short posts called tweets. Users in Twitter can follow other users, called followees. A user can see the posts of his followees on his Twitter profile home page. An information overload problem arose, with the increase of the number of followees, related to the number of tweets available in the user page. Twitter, similar to other social network websites, attempts to elevate the tweets the user is expected to be interested in to increase overall user engagement. However, Twitter still uses the chronological order to rank the tweets. The tweets ranking problem was addressed in many current researches. A sub-problem of this problem is to rank the tweets for a single followee. In this paper we represent the tweets using several features and then we propose to use a weighted version of the famous voting system Borda-Count (BC) to combine several ranked lists into one. A gradient descent method and collaborative filtering method are employed to learn the optimal weights. We also employ the Baldwin voting system for blending features (or predictors). Finally we use the greedy feature selection algorithm to select the best combination of features to ensure the best results.

Nephrotoxicity and nephrocarcinogenicity of dinitrotoluene : new aspects to be considered

Technical dinitrotoluene (DNT) is a mixture of 2,4- and 2,6-DNT. In humans, industrial or environmental exposure can occur orally, by inhalation, or by skin contact. The classification of DNT as an 'animal carcinogen' is based on the formation of malignant tumors in kidneys, liver, and mammary glands of rats and mice. Clear signs of toxic nephropathy were found in rats dosed with DNT, and the concept was derived of an interrelation between renal toxicity and carcinogenicity. Recent data point to the carcinogenicity of DNT on the urinary tract of exposed humans. Between 1984 and 1997, 6 cases of urothelial cancer and 14 cases of renal cell cancer were diagnosed in a group of 500 underground mining workers in the copper mining industry of the former GDR and having high exposures to explosives containing technical DNT. The incidences of both urothelial and renal cell tumors in this group were 4.5 and 14.3 times higher, respectively, than anticipated on the basis of the cancer registers of the GDR. The genotyping of all identified tumor patients for the polymorphic enzymes NAT2, GSTM1, and GSTT1 identified the urothelial tumor cases as exclusively 'slow acetylates'. A group of 161 miners highly exposed to DNT was investigated for signs of subclinical renal damage. The exposures were categorized semi-quantitatively into 'low', 'medium', 'high', and 'very high'. A straight dose-dependence of the excretion of urinary biomarker proteins with the ranking of exposure was seen. Biomarker excretion (alpha1-microglobulin, glutathione S-transferases alpha and pi) indicated that DNT-induced damage was directed toward the tubular system. New data on DNT-exposed humans appear consistent with the concept of cancer initiation by DNT isomers and the subsequent promotion of renal carcinogenesis by selective damage to the proximal tubule. The differential pathways of metabolic activation of DNT appear to apply to the proximal tubule of the kidney and to the urothelium of the renal pelvis and lower urinary tract as target tissues of carcinogenicity.

Pathological excretion patterns of urinary proteins in miners highly exposed to dinitrotoluene

A cohort of 161 underground miners who had been highly exposed to dinitrotoluene (DNT) in the copper-mining industry of the former German Democratic Republic was reinvestigated for signs of subclinical renal damage. The study included a screening of urinary proteins excreted by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), and quantitations of the specific urinary proteins α 1-microglobulin and glutathione-S-transferase α (GST α) as biomarkers for damage of the proximal tubule and glutathione-S-transferase π (GST π) for damage of the distal tubule. The exposures were categorized semiquantitatively (low, medium, high, and very high), according to the type and duration of professional contact with DNT. A straight dose-dependence of pathological protein excretion patterns with the semiquantitative ranking of DNT exposure was seen. Most of the previously reported cancer cases of the urinary tract, especially those in the higher exposed groups, were confined to pathological urinary protein excretion patterns. The damage from DNT was directed toward the tubular system. In many cases, the appearance of Tamm-Horsfall protein, a 105-kD protein marker, was noted. Data on the biomarkers α 1-microglobulin, GST α, and GST π consistently demonstrated a dose-dependent increase in tubular damage, which confirmed the results of screening by SDS-PAGE and clearly indicated a nephrotoxic effect of DNT under the given conditions of exposure. Within the cluster of cancer patients observed among the DNT-exposed workers, only in exceptional cases were normal biomarker excretions found.

Hydrolysis of genotoxic methyl-substituted oxiranes : Experimental kinetic and semiempirical studies

The kinetics of acid-catalyzed hydrolysis of seven methylated aliphatic epoxides - R1R2C(O)CR3R4 (A: R1=R2=R3=R4=H; B: R1=R2=R3=H, R4=Me; C: R1=R2=H, R3=R4=Me; D: R1=R3=H, R2=R4=Me(trans); E: R1=R3=H, R2=R4=Me(cis); F: R1=R3=R4=Me, R2=H; G: R1=R2=R3=R4=Me) - has been studied at 36 ± 1.5°C. Compounds with two methyl groups at the same carbon atom of the oxirane ring exhibit highest rate constants (k(eff) in reciprocal molar concentration per second: 11.0 ± 1.3 for C, 10.7 ± 2.1 for F, and 8.7 ± 0.7 for G as opposed to 0.124 ± 0.003 for B, 0.305 ± 0.003 for D, and 0.635 ± 0.036 for E). Ethylene oxide (A) displays the lowest rate of hydrolysis (0.027 M-1 s-1). The results are consistent with literature data available for compounds A, B, and C. To model the reactivities we have employed quantum chemical calculations (MNDO, AM1, PM3, and MINDO/3) of the main reaction species. There is a correlation of the logarithm k(eff) with the total energy of epoxide ring opening. The best correlation coefficients (r) were obtained using the AM1 and MNDO methods (0.966 and 0.957, respectively). However, unlike MNDO, AM1 predicts approximately zero energy barriers for the oxirane ring opening of compounds B, C, E and G, which is not consistent with published kinetic data. Thus, the MNDO method provides a preferential means of modeling the acidic hydrolysis of the series of methylated oxiranes. The general ranking of mutagenicity in vitro, A > B > C, is in line with the concept that this sequence also gradually leaves the expoxide reactivity optimal for genotoxicity toward reactivities leading to higher biological detoxifications.

Benefits of integrating complementarity into priority threat management

Conservation decision tools based on cost-effectiveness analysis are used to assess threat management strategies for improving species persistence. These approaches rank alternative strategies by their benefit to cost ratio but may fail to identify the optimal sets of strategies to implement under limited budgets because they do not account for redundancies. We devised a multi objective optimization approach in which the complementarity principle is applied to identify the sets of threat management strategies that protect the most species for any budget. We used our approach to prioritize threat management strategies for 53 species of conservation concern in the Pilbara, Australia. We followed a structured elicitation approach to collect information on the benefits and costs of implementing 17 different conservation strategies during a 3-day workshop with 49 stakeholders and experts in the biodiversity, conservation, and management of the Pilbara. We compared the performance of our complementarity priority threat management approach with a current cost-effectiveness ranking approach. A complementary set of 3 strategies: domestic herbivore management, fire management and research, and sanctuaries provided all species with >50% chance of persistence for $4.7 million/year over 20 years. Achieving the same result cost almost twice as much ($9.71 million/year) when strategies were selected by their cost-effectiveness ranks alone. Our results show that complementarity of management benefits has the potential to double the impact of priority threat management approaches.

Ranking based clustering for social event detection

The problem of clustering a large document collection is not only challenged by the number of documents and the number of dimensions, but it is also affected by the number and sizes of the clusters. Traditional clustering methods fail to scale when they need to generate a large number of clusters. Furthermore, when the clusters size in the solution is heterogeneous, i.e. some of the clusters are large in size, the similarity measures tend to degrade. A ranking based clustering method is proposed to deal with these issues in the context of the Social Event Detection task. Ranking scores are used to select a small number of most relevant clusters in order to compare and place a document. Additionally,instead of conventional cluster centroids, cluster patches are proposed to represent clusters, that are hubs-like set of documents. Text, temporal, spatial and visual content information collected from the social event images is utilized in calculating similarity. Results show that these strategies allow us to have a balance between performance and accuracy of the clustering solution gained by the clustering method.

The contribution of major depression to the global burden of ischemic heart disease : a comparative risk assessment

Background Cardiovascular disease and mental health both hold enormous public health importance, both ranking highly in results of the recent Global Burden of Disease Study 2010 (GBD 2010). For the first time, the GBD 2010 has systematically and quantitatively assessed major depression as an independent risk factor for the development of ischemic heart disease (IHD) using comparative risk assessment methodology. Methods A pooled relative risk (RR) was calculated from studies identified through a systematic review with strict inclusion criteria designed to provide evidence of independent risk factor status. Accepted case definitions of depression include diagnosis by a clinician or by non-clinician raters adhering to Diagnostic and Statistical Manual of Mental Disorders (DSM) or International Classification of Diseases (ICD) classifications. We therefore refer to the exposure in this paper as major depression as opposed to the DSM-IV category of major depressive disorder (MDD). The population attributable fraction (PAF) was calculated using the pooled RR estimate. Attributable burden was calculated by multiplying the PAF by the underlying burden of IHD estimated as part of GBD 2010. Results The pooled relative risk of developing IHD in those with major depression was 1.56 (95% CI 1.30 to 1.87). Globally there were almost 4 million estimated IHD disability-adjusted life years (DALYs), which can be attributed to major depression in 2010; 3.5 million years of life lost and 250,000 years of life lived with a disability. These findings highlight a previously underestimated mortality component of the burden of major depression. As a proportion of overall IHD burden, 2.95% (95% CI 1.48 to 4.46%) of IHD DALYs were estimated to be attributable to MDD in 2010. Eastern Europe and North Africa/Middle East demonstrate the highest proportion with Asia Pacific, high income representing the lowest. Conclusions The present work comprises the most robust systematic review of its kind to date. The key finding that major depression may be responsible for approximately 3% of global IHD DALYs warrants assessment for depression in patients at high risk of developing IHD or at risk of a repeat IHD event.

The burden attributable to mental and substance use disorders as risk factors for suicide : findings from the Global Burden of Disease Study 2010

Background The Global Burden of Disease Study 2010 (GBD 2010) identified mental and substance use disorders as the 5th leading contributor of burden in 2010, measured by disability adjusted life years (DALYs). This estimate was incomplete as it excluded burden resulting from the increased risk of suicide captured elsewhere in GBD 2010's mutually exclusive list of diseases and injuries. Here, we estimate suicide DALYs attributable to mental and substance use disorders. Methods Relative-risk estimates of suicide due to mental and substance use disorders and the global prevalence of each disorder were used to estimate population attributable fractions. These were adjusted for global differences in the proportion of suicide due to mental and substance use disorders compared to other causes then multiplied by suicide DALYs reported in GBD 2010 to estimate attributable DALYs (with 95% uncertainty). Results Mental and substance use disorders were responsible for 22.5 million (14.8-29.8 million) of the 36.2 million (26.5-44.3 million) DALYs allocated to suicide in 2010. Depression was responsible for the largest proportion of suicide DALYs (46.1% (28.0%-60.8%)) and anorexia nervosa the lowest (0.2% (0.02%-0.5%)). DALYs occurred throughout the lifespan, with the largest proportion found in Eastern Europe and Asia, and males aged 20-30 years. The inclusion of attributable suicide DALYs would have increased the overall burden of mental and substance use disorders (assigned to them in GBD 2010 as a direct cause) from 7.4% (6.2%-8.6%) to 8.3% (7.1%-9.6%) of global DALYs, and would have changed the global ranking from 5th to 3rd leading cause of burden. Conclusions Capturing the suicide burden attributable to mental and substance use disorders allows for more accurate estimates of burden. More consideration needs to be given to interventions targeted to populations with, or at risk for, mental and substance use disorders as an effective strategy for suicide prevention.